Trend analysis of global stock market linkage based on a dynamic conditional correlation network

Abstract

The paper analyses the trend of global stock market linkages via daily data of 51 stock indices spanning the period 22 July 2005 to 30 June 2016 which covers four regions: America, Europe, Asia Pacific and Africa. A dynamic conditional multivariate generalized autoregressive conditional heteroskedasticity (DCC-MVGARCH) approach was used to calculate dynamic correlation coefficient in order to construct the volatility networks. The methods of minimum spanning tree (MST) and low pass filter were for the first time applied to analyze the variable periodicity of the comovement. The original contribution of this paper is that contrary to previous works, financial events such as Quantitative Easing (QE) and Bailouts are accounted for rather than only crisis factors such as the 2008 financial crisis and the European Debt crisis. The main findings of the paper are as follows: (1) Financial crisis promotes and strengthens global stock markets linkage in the short run; (2) Linkage cycles post crisis are significantly short, due to the effect of monetary policy spillover effects caused by QE from developed to developing countries; and (3) European stock markets are the information transmission hub for global stock market. The research conclusions would be significant for both government to regulate markets as well as for investors to diversify risks.

Keywords:

• complex network
• DCC-MVGARCH
• topological properties
• minimum spanning tree
• low pass filter
• variable periodicity analysis

JEL Classification:

• C15
• C61
• E32
• G01
• G14
• G15

Additional information

Notes on contributors

Kedong Yin

Kedong YIN, received the B.S. degree in system engineering from Nanjing University of Science and Technology, Nanjing, China, in 1988, M.S. degree in economics from Ocean University of China, Qingdao, China, in 1997, and PhD degree in business administration from Huazhong University of Science and Technology, Wuhan, China, in 2009. He is currently a Professor with the School of Economics, Ocean University of China, Shandong, China. He has authored or coauthored more than 100 publications. His research interests focus on quantitative economic analysis and modeling, financial risk management, and marine econometrics.

Zhe Liu

Zhe LIU, received the B.S. degree in mathematical economics from Shandong University. He is currently a graduate student at the School of Economics, Ocean University of China, Shandong, China. His research interests includes financial risk management, data mining and artificial intelligence.

Peide Liu

Peide LIU, received the B.S. and M.S. degrees in signal and information processing from Southeast University, Nanjing, China, in 1988 and 1991, respectively, and the PhD degree in information management from Beijng Jiaotong University, Beijing, China, in 2010. He is currently a Professor with the School of Management Science and Engineering, Shandong University of Finance and Economics, Shandong, China. He is an Associate Editor of the Journal of Intelligent and Fuzzy Systems, the member of editorial board of the journal Technological and Economic Development of Economy, and the members of editorial board of the other 12 journals. He has authored or coauthored more than 150 publications. His research interests include aggregation operators, fuzzy logic, fuzzy decision making, and their applications.